In order to obtain magnetic resonance-based recordings, in other words image data generated using a magnetic resonance tomography system, from a region inside the body of an examination object, the body or the part of the body to be examined must first be exposed to the most homogeneous static basic magnetic field possible, generally referred to as a B0 field. This aligns the nuclear spins in the body parallel to the direction of the B0 field (generally referred to as the z direction).
Also suitable high-frequency antennas are used to radiate high-frequency pulses (HF pulses) into the examination object, their frequency being in the region of the resonant frequency, the so-called Larmor frequency, of the nuclei to be excited in the magnetic field present. These high-frequency pulses are used to excite the spins of the nuclei to be excited, generally hydrogen nuclei, in the examination object in such a manner that they are deflected through a so-called excitation flip angle from their equilibrium position parallel to the basic magnetic field B0. The nuclear spins precess first around the z direction and then gradually relax, relaxation being a function of the molecular environment, in which the excited nucleus is located. The magnetic resonance signals generated during relaxation are picked up as so-called raw data by means of high-frequency receive antennas and the magnetic resonance images are ultimately reconstructed on the basis of the acquired raw data. Spatial encoding takes place with the aid of rapidly switching gradient magnetic fields, which are superimposed on the basic magnetic field during the emission of the high-frequency magnetic resonance pulses and/or the acquisition of the raw data.
A generally known fundamental problem with the acquisition of the raw data is that the excited nuclei in the body tissue do not have a uniform resonant frequency in the magnetic field but can differ according to their chemical environment for different tissue or substance types. This is generally referred to as chemical displacement. A substance type (or substance for short) refers in the following in the context of the invention to any type of predefined chemical substance or any type of atom or molecule nucleus with certain magnetic resonance behaviors. The substance types fat and water are a typical example of different substance types. A substance type here can contain a number of components which have (slightly) different resonant frequencies, for example when the substance type, as described in more detail below, can be described by a chemical spectral model with a number of peaks in respect of resonant frequency. The different substance types therefore also refer to more complex chemical compounds or mixtures, the different components of which in some instances have different resonant frequencies but make up a characteristic spectrum. Of particular relevance in magnetic resonance imaging is the chemical displacement of fat tissue in relation to the normally excited water, as in many body regions fat is present in considerable quantities. The chemical displacement between fat tissue and water is approx. 3.4 ppm.
In the meantime there are various methods for creating separate magnetic resonance images for different substance types, for example for generating separate water and fat images. One typical method for this is the so-called two-point Dixon method. For this suitable magnetic resonance sequences are used to record raw data by means of two different echoes, for example two different gradient echoes or spin echoes, said echoes differing in their echo time, so that for one echo the phasing of the water corresponds to the phasing of the fat, while for the second echo the phasing of the water is aligned counter to the phasing of the fat. This is possible if the echo times are determined exactly beforehand and the magnetic resonance sequences are structured accordingly. After signal processing and standard Fourier transformation for reconstructing image data from the raw data, two different types of magnetic resonance image data result, specifically image data with corresponding phasing, the so-called in-phase image, and image data with counter phasing, the so-called opposed-phase image. The signal values in both images can be written as follows ignoring the tissue relaxation:S0(v)=(W(v)+F(v))eiφ0  (1)S1(v)=(W(v)−F(v))ei(φ0-φ)  (2)
In these equations the water portion and fat portion are represented in a given image point by W(v) or, as the case may be, F(v). S0(v) and S1(v) are the intensity values in the in-phase image and in the opposed-phase image at the respective image point. An image point here and in the following refers in the case of two-dimensional image data to a pixel and in the case of three-dimensional image data to a voxel. v here represents the coordinates of the image point (i.e. v=(x,y,z), when x, y and z respectively are the coordinates along the x axis, y axis and z axis). The unit in which the spatial coordinates are given can be defined for example simply by the number of image points in the respective direction. The value φ0 gives the phase in the image that results due to field inhomogeneities and a static phase error that can occur in the signal and receive chain. The phase rotation or phase φ represents a further phase error mainly due to the field inhomogeneity that results between the in-phase and opposed-phase echo. In between are various algorithms for generating the water image W and fat image F from the in-phase image and opposed-phase image using the equations (1) and (2). Because of possible field inhomogeneities, gradient delays, eddy currents, etc. it is very important for the two-point Dixon method to determine the overall phase rotation φ between the two echo times per image point and then take it into account in the reconstruction. Generally it is assumed for this purpose that the phase rotation variation is spatially weak, in other words the variation between adjacent image points is for example <180°.
One major disadvantage of this two-point Dixon method is the restriction to quite precisely defined echo times. This significantly reduces freedoms when developing appropriate magnetic resonance sequences. It is then no longer possible to match the echo times to other conditions, in order for example to develop a particularly fast magnetic resonance sequence in order to achieve an optimum signal to noise ratio, etc.
In the article by Holger Eggers et al. “Dual-Echo Dixon Imaging with Flexible Choice of Echo Times” in Magnetic Resonance in Medicine 65, pages 96 to 107, 2011, a method is described, in which the echo times can be selected in a more flexible manner. However as before a relatively simple model is used for fat, in which it is assumed that fat has precisely one resonant frequency line. In fact however fat, like many other substance types, has a plurality of resonant frequencies very close together, in other words should really be described by a multi-peak spectral model. In EP 2 431 760 A1 therefore Eggers describes a method, in which such a multi-peak spectral model can be used for fat, with the result however that the overall mathematical description becomes much more complicated compared with the known conventional method. In order ultimately to arrive at a water image or fat image, it is therefore proposed in EP 2 431 760 A1 that first all the voxels for which there is a unique mathematical solution should be identified and then the non-uniqueness should be resolved for the other voxels. The voxels with unique solutions identified in the direct vicinity are then used. In order to achieve this, a correspondingly large number of voxels in which such a mathematically unique solution exists is required in the images. To this end it is demonstrated that it is possible to influence the number of voxels with unique solutions by selecting the echo times appropriately. This has the disadvantage that although the echo times are not set exactly—unlike with the conventional method—there is still a not inconsiderable restriction in respect of the selection of echo times.